IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v186y2024ics1366554524001571.html
   My bibliography  Save this article

On the planning of zone-based electric on-demand minibus

Author

Listed:
  • Wang, Tao
  • Guo, Jia
  • Zhang, Wei
  • Wang, Kai
  • Qu, Xiaobo

Abstract

An on-demand transportation system can enhance traffic efficiency through its flexible services. In this study, we introduce a planning problem for an on-demand electric minibus service within urban areas. We are considering a zone-based operation, meaning that the on-demand minibus is restricted to picking up or dropping off passengers within a single zone for each trip, and the minibus does not stop in other zones. For this zonal electric minibus system, we plan the service level for each zone, the construction of dedicated charging piles in each zone, and the optimal size of the bus fleet. To model the planning problem, we propose a mixed-integer nonlinear second-order cone program. Additionally, we introduce an adaptive discretization algorithm to expedite the problem-solving process. Our numerical tests illustrate the planning for the on-demand minibus system in Manhattan. Furthermore, these tests underscore the benefits of the proposed on-demand minibus system. The most important findings of this study are: (i) the proposed mode replaces more trips with cars, thus reducing the traffic flow and alleviating traffic congestion; (ii) the service zone division, the setting of the fare, and the number of seats in minibus play an essential role in the revenue of the on-demand minibus system; (iii) considering endogenous zone selecting, number of dedicated charging piles, and mode choice in each zone is essential to the planning of the on-demand minibus system.

Suggested Citation

  • Wang, Tao & Guo, Jia & Zhang, Wei & Wang, Kai & Qu, Xiaobo, 2024. "On the planning of zone-based electric on-demand minibus," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:transe:v:186:y:2024:i:c:s1366554524001571
    DOI: 10.1016/j.tre.2024.103566
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554524001571
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2024.103566?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Guo, Xiaotong & Caros, Nicholas S. & Zhao, Jinhua, 2021. "Robust matching-integrated vehicle rebalancing in ride-hailing system with uncertain demand," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 161-189.
    2. Xu, Zhengtian & Yin, Yafeng & Chao, Xiuli & Zhu, Hongtu & Ye, Jieping, 2021. "A generalized fluid model of ride-hailing systems," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 587-605.
    3. Long He & Ho-Yin Mak & Ying Rong & Zuo-Jun Max Shen, 2017. "Service Region Design for Urban Electric Vehicle Sharing Systems," Manufacturing & Service Operations Management, INFORMS, vol. 19(2), pages 309-327, May.
    4. Daniel Adelman, 2007. "Price-Directed Control of a Closed Logistics Queueing Network," Operations Research, INFORMS, vol. 55(6), pages 1022-1038, December.
    5. Çavdar, Bahar & Sokol, Joel, 2015. "A distribution-free TSP tour length estimation model for random graphs," European Journal of Operational Research, Elsevier, vol. 243(2), pages 588-598.
    6. Wang, Xiaolei & He, Fang & Yang, Hai & Oliver Gao, H., 2016. "Pricing strategies for a taxi-hailing platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 212-231.
    7. Kang, Liujiang & Sun, Huijun & Wu, Jianjun & Gao, Ziyou, 2020. "Last train station-skipping, transfer-accessible and energy-efficient scheduling in subway networks," Energy, Elsevier, vol. 206(C).
    8. Zhong, Yuanguang & Yang, Tong & Cao, Bin & Cheng, T.C.E., 2022. "On-demand ride-hailing platforms in competition with the taxi industry: Pricing strategies and government supervision," International Journal of Production Economics, Elsevier, vol. 243(C).
    9. (Edward) Kim, Myungseob & Levy, Joshua & Schonfeld, Paul, 2019. "Optimal zone sizes and headways for flexible-route bus services," Transportation Research Part B: Methodological, Elsevier, vol. 130(C), pages 67-81.
    10. Sun, Hao & Wang, Hai & Wan, Zhixi, 2019. "Model and analysis of labor supply for ride-sharing platforms in the presence of sample self-selection and endogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 76-93.
    11. Aarhaug, Jørgen & Olsen, Silvia, 2018. "Implications of ride-sourcing and self-driving vehicles on the need for regulation in unscheduled passenger transport," Research in Transportation Economics, Elsevier, vol. 69(C), pages 573-582.
    12. Lin Wang & S. C. Wirasinghe & Lina Kattan & Saeid Saidi, 2018. "Optimization of demand-responsive transit systems using zonal strategy," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 22(3), pages 366-381, July.
    13. Cong, Yuan & Wang, Heqi & Bie, Yiming & Wu, Jiabin, 2023. "Double-battery configuration method for electric bus operation in cold regions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    2. Zhang, Yufeng & Khani, Alireza, 2021. "Integrating transit systems with ride-sourcing services: A study on the system users’ stochastic equilibrium problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 95-123.
    3. Hu, Xinru & Zhou, Shuiyin & Luo, Xiaomeng & Li, Jianbin & Zhang, Chi, 2024. "Optimal pricing strategy of an on-demand platform with cross-regional passengers," Omega, Elsevier, vol. 122(C).
    4. Rathore, Bhawana & Sengupta, Pooja & Biswas, Baidyanath & Kumar, Ajay, 2024. "Predicting the price of taxicabs using Artificial Intelligence: A hybrid approach based on clustering and ordinal regression models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    5. He, Shan & Dai, Ying & Ma, Zu-Jun, 2023. "To offer or not to offer? The optimal value-insured strategy for crowdsourced delivery platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    6. Liu, Yang & Li, Sen, 2023. "An economic analysis of on-demand food delivery platforms: Impacts of regulations and integration with ride-sourcing platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    7. Zhu, Zheng & Xu, Ailing & He, Qiao-Chu & Yang, Hai, 2021. "Competition between the transportation network company and the government with subsidies to public transit riders," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    8. Yang, Hai & Qin, Xiaoran & Ke, Jintao & Ye, Jieping, 2020. "Optimizing matching time interval and matching radius in on-demand ride-sourcing markets," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 84-105.
    9. Long He & Guangrui Ma & Wei Qi & Xin Wang, 2021. "Charging an Electric Vehicle-Sharing Fleet," Manufacturing & Service Operations Management, INFORMS, vol. 23(2), pages 471-487, March.
    10. Zhang, Kenan & Nie, Yu (Marco), 2021. "To pool or not to pool: Equilibrium, pricing and regulation," Transportation Research Part B: Methodological, Elsevier, vol. 151(C), pages 59-90.
    11. Li, Baicheng & Szeto, W.Y. & Luo, Qin, 2021. "A peak-period taxi scheme design problem: Formulation and policy implications," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    12. Long Gao & Jim (Junmin) Shi & Michael F. Gorman & Ting Luo, 2020. "Business Analytics for Intermodal Capacity Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 310-329, March.
    13. Ke, Jintao & Yang, Hai & Li, Xinwei & Wang, Hai & Ye, Jieping, 2020. "Pricing and equilibrium in on-demand ride-pooling markets," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 411-431.
    14. Mo, Dong & Yu, Jingru & Chen, Xiqun Michael, 2020. "Modeling and managing heterogeneous ride-sourcing platforms with government subsidies on electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 447-472.
    15. He, Qiaochu & Fan, Xiaoshuai & Chen, Ying-Ju & Yang, Hai, 2021. "On-demand service delivery under asymmetric information: Priority pricing, market selection, and horizontal substitution," International Journal of Production Economics, Elsevier, vol. 237(C).
    16. Xudong Li & Zhongzhen Yang & Feng Lian, 2023. "Optimizing On-Demand Bus Services for Remote Areas," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    17. Keith, David R. & Naumov, Sergey & Rakoff, Hannah E. & Sanches, Lars Meyer & Singh, Anuraag, 2024. "The effect of increasing vehicle utilization on the automotive industry," European Journal of Operational Research, Elsevier, vol. 317(3), pages 776-792.
    18. Zhang, Kenan & Nie, Yu (Marco), 2022. "Mitigating traffic congestion induced by transportation network companies: A policy analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 96-118.
    19. Huang, Guan & Liang, Yuebing & Zhao, Zhan, 2023. "Understanding market competition between transportation network companies using big data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    20. Yang, Chao & Chen, Zhuoran & Qian, Jianghai & Han, Dingding & Zhao, Kaidi, 2023. "Simultaneous improvement of multiple transportation performances on link-coupled networks by global dynamic routing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:186:y:2024:i:c:s1366554524001571. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.